中国证券市场价值溢价实证研究

以1995年7月—2005年12月我国证券市场深沪两市的上市公司为样本,考察了价值溢价随规模变化的规律,并检验了CAPM能否解释价值溢价以及与权益帐面市值比B/M(或规模)无关的贝塔(β)能否与股票的平均收益相补偿.实证检验发现:1)中国股市存在一定程度的价值溢价,尤其是小规模(S ize)价值股在平均收益上存在着明显的价值溢价,而大规模(S ize)价值股则不存在价值溢价现象.2)CAPM能够解释我国股市从1995年7月至2005年12月期间的价值溢价.     

基于条件贝塔信息对横截面收益的解释

以1995年6月-2005年12月期间在我国沪深A股市场上市的全部股票为样本,本文实证发现,FF三因子模型不能对横截面收益作出合理的解释。为了基于现代金融理论的基本观点对横截面收益现象作出更为合理的解释,本文利用贝塔条件变化信息对无条件的FF三因子模型进行改进,实证发现,改进后的条件定价模型对横截面收益的解释力提高了,并且该解释力在2006年1月-2008年5月、1995年6月-2008年5月期间均具有稳健性。由此得出结论认为,在解释横截面收益时,贝塔条件变化的条件定价模型是一个优于无条件FF三因子模型的模型。     

从投资情绪角度看股票市场流动性——来自B股向境内居民开放的研究

我们借鉴行为方面的模型,即投资情绪的变化会影响股票市场的流动性,从而影响股票的未来收益。在卖空限制条件下市场高流动性预示市场充斥着非理性投资者。本文通过中国股市具备卖空限制和2001年2月B股向境内居民开放前后B股投资主体(投资情绪)发生变化这一自然事件,实证分析了B股市场向境内居民开放后,投资者情绪变化引起市场流动性增加,对股票预期收益的流动性溢价影响也由开放前的不显著变化为显著。     

贝塔系数变动性的多重分形特征及其量化方法

针对CAPM模型中贝塔系数的时变性观点,本文提出了多重分形去趋势贝塔分析法(MFDBCA),运用该方法检验上证综合A股指数、上证综合B股指数、深圳综指、深圳综合A股指数及深圳综合B股指数的贝塔系数变动性,并对其多重分形程度进行了量化分析,分析了其在投资实践中应用。研究结果表明:它们的贝塔系数变动性呈现出多重分形特征,上证综合A股指数的多重分形程度最小,而上证综合B股指数的多重分形程度最大。本文研究为量化系统风险及利用贝塔投资实践提供了一种新方法,为改进贝塔系数提供了一种猜想。     

我国A股市场投资者情绪是定价因子吗?

以股票价格变化的强弱和方向反映投资者的心理预期,选取流通性指标作为股票交易强弱的指标,股票买卖行为的人气指标作为投资交易方向的指标,从交易强弱和交易方向两个角度构建了投资者情绪综合指标(简记为ISI).选取2006年1月至2017年6月沪市A股上市公司为样本,进行了ISI与股票收益的时间序列分析和截面效应分析.研究结果表明,投资者情绪综合指标提高了预期收益率但降低了本期收益率,预期收益率具有显著的正向风险溢价.ISI自身也具有显著的正向风险溢价,对股票市场超额收益具有很好的解释能力.投资者情绪指标是中国股市一个重要的资产定价因子.     

股权分置改革试点G股的超常收益实证研究

本文采用事件研究法就股权分置试点改革过程中G股股票是否存在超常收益进行了实证分析。实证分析表明股改试点公司股票在试点公司完成股改后复牌当天确实存在着显著的正的超常收益,其中第一批试点公司G股股票的平均超常收益率高于第二批试点公司G股股票的平均超常收益率,深交所试点公司G股股票的平均超常收益率略高于上交所试点公司G股股票的平均超常收益率,中小企业板试点公司G股股票的平均超常收益率高于主板试点公司G股股票的平均超常收益率,高对价试点公司G股股票的平均超常收益率高于低对价试点公司G股股票的平均超常收益率。     

计算股市的基本方程、理论和原理(Ⅲ)——基本理论

由基本方程导出两个理论:1 股票的价值理论v*(t)=v(0)exp(ar₂t)。2 股能守恒理论。将股能定义为股价v及其导数v>的二次函数φ=Av2+Bvv+Cv2+Dv,在基本方程约束下,将问题归结为沿最优路径的约束优化问题。应用Lagrange乘数,变分法Euler方程可证?对任何v、v>守恒。文中给出应用这些方程和理论对股市走势作分析的一些判断并为深沪股市实际走势所验证。     

系统性尾部贝塔与市场崩盘风险的对冲:基于崩盘风险的“安全第一准则”投资组合均衡模型

近年来随着市场震荡多变,我国A股市场频繁出现千股跌停的现象。如何在市场发生崩盘风险的情形下,预测风险资产的尾部风险,并有效对冲市场崩盘风险等问题引起了广泛的关注。为了回答这些问题,论文在传统“安全第一准则”投资组合模型中引入了市场发生崩盘风险的约束条件,在均衡情形下获得了具有市场崩盘风险的资产定价模型(Crash CAPM:CCAPM),利用CCAPM中风险负载与传统的市场贝塔,论文构建了一个新的系统性尾部风险度量指标β~Δ。利用1995—2018年期间我国A股市场日收益率数据进行实证检验发现,β~Δ能够有效地捕捉到市场崩盘与繁荣时期,资产与市场的尾部关联性。特别地,在市场崩盘时期,β△与风险资产极端损失风险呈显著的正相关关系,高β~Δ组合与低β~Δ组合之差构建的投资组合,在市场崩盘时期,能够获得显著为正的尾部超额收益率,这为对冲市场崩盘提供了重要的依据。     

PLS情绪指数对中国股市风险收益关系的影响研究

从行为金融学角度研究投资者情绪对中国股市风险收益关系的影响,或有助于更好的解释风险收益关系.采用偏最小二乘法(PLS)构建新的投资者情绪综合指数,同时在对风险的度量中运用个股平均相关性代替总体方差来度量市场风险.研究结果表明PLS情绪指数比常用的主成分分析法所构建的情绪指数及单个情绪代理变量能更好的解释股市收益;平均相关性比市场波动更适合作为市场风险的度量指标;投资者情绪对风险收益关系有显著影响,其中在低情绪期风险和收益之间的相关性不显著,而高情绪期风险和收益之间呈现显著的负相关关系.由实证结果可知中国股市投资者存在非理性行为,应从行为金融的角度去考虑资产定价,同时对各指标的准确度量更有利于完善行为资产定价理论.     

中国股票市场的分形结构——股票收益长期记忆特征的实证研究

股票市场收益的长期记忆特征对于系统非线性结构的确定以及市场有效性的研究具有重要的意义.针对上海和深圳A股算术加权和流通市值加权市场指数的周收益序列以及上证180指数和深圳成份指数中选取的12只代表性股票的周收益序列,采用重标级差分析(R/S分析)和ARF IM A模型对其进行了实证研究.从统计结果来看,样本序列呈现出尖峰和肥尾等有偏特征,明显不满足正态分布的假设,表明收益序列可能具有长程相关或记忆性.进一步的研究发现,沪深两市A股市场指数收益序列和大多数个股(10只股票)存在明显的长期记忆特征,收益分布表现出持久性.从划分不同时段的分析结果来看,中国股票市场渐进趋于弱势有效.     

Empirical analysis on risk of security investment

The paper analyzes the theory and application of Markowitz Mean-Variance Model and CAPM model. Firstly, it explains the development process and standpoints of two models and deduces the whole process in detail. Then 30 stocks are choosen from Shangzheng 50 stocks and are testified whether the prices of Shanghai stocks conform to the two models. With the technique of time series and panel data analysis, the research on the stock risk and effective portfolio by ORIGIN and MATLAB software is conducted. The result shows that Shanghai stock market conforms to Markowitz Mean-Variance Model to a certain extent and can give investors reliable suggestion to gain higher return, but there is no positive relation between system risk and profit ratio and CAPM doesn＇t function well in China＇s security market.     

股市风险构成间接分解模型的改进及实证

对Campbell等提出的分析股市风险构成的间接分解模型进行改进,并运用改进模型研究中国股票市场1995年至2005年的风险构成和趋势。结果发现,公司风险是个股收益率平均风险的最大组成部分,其次是系统风险,行业风险的重要性相对较小;中国股市收益率的平均风险随时间存在下降的趋势,而公司风险和行业风险的重要性随时间在增加;总的协方差风险序列对个股收益率平均风险的影响,随时间不具有一致性。在分析股市风险构成时,不应忽略对协方差风险序列的研究。     

Run lengths and liquidity

We develop a market-wide illiquidity risk factor based on run lengths and find that it is priced using standard asset-pricing specifications. Our theoretical framework of equity returns derives the result that average run lengths of individual stocks proxy for illiquidity, and are related to common measures of liquidity such as trading volume and trade price-impact. This relationship holds irrespective of the sampling frequency in the computation of run lengths. Thus, liquidity can be quantified by examining a stock’s run length signature, providing a statistical mechanics link across illiquidity metrics. Tests using daily equity return data for all stocks over the period 1962–2005 find that run lengths are decreasing in turnover, and increasing with bid-ask spreads, and price-impact. Illiquidity is shown to be a risk factor/characteristic in explaining equity returns.     

A new test on the conditional capital asset pricing model

Testing the validity of the conditional capital asset pricing model(CAPM) is a puzzle in the finance literatureLewellen and Nagel[14]find that the variation in betas and in the equity premium would have to be implausibly large to explain important asset-pricing anomaliesUnfortunately, they do not provide a rigorous test statisticBased on a simulation study, the method proposed in Lewellen and Nagel[14]tends to reject the null too frequently.We develop a new test procedure and derive its limiting distribution under the null hypothesis.Also, we provide a Bootstrap approach to the testing procedure to gain a good finite sample performanceBoth simulations and empirical studies show that our test is necessary for making correct inferences with the conditional CAPM.     

The behavior of individual and aggregate stock prices

News about an individual stock normally has only a trivial impact on the aggregate economy. The news of the aggregate stock market, however, may have a significant impact on the prospects of the economy, and so has a large impact on the pricing kernel. This difference between the aggregate stock market and individual stocks is analyzed in a dynamic general equilibrium setting with incomplete information. The main findings are as follows. First, consistent with existing empirical evidence, the correlation between stock returns and earnings surprises is, on average, positive at the individual stock level and is lower or even negative at the aggregate level. Second, a stock’s return is less sensitive to its earnings surprises if the expected earnings growth of the stock is more pro-cyclical. Third, a decrease of information quality of a stock increases its risk premium if the stock accounts for a small fraction of the economy, but decreases its risk premium if the stock accounts for a large fraction.     

The informational content of insider trading disclosures: empirical results for the Polish stock market

In this paper, we try to answer the question as to whether insider trading disclosures convey valuable information to market participants, valuable in the sense of the profitability of an investment strategy that faithfully mirrors insider behaviour. Our interest in this subject is limited to the case of announcements concerning insider transactions issued over a 6 year-period on the Warsaw Stock Exchange (WSE). Initially, we use event study methodology to check whether insider trading disclosures are accompanied by a performance of stock returns as well as trading volume. Two different models generating expected returns (expected volume) are employed to verify the robustness of our results. The first of these is the regime switching model, with the results then being recalculated by using a GARCH-type model which seem to be most useful for dealing with some of the inconvenient statistical properties of stock return and trading volume data. Afterwards, a technique based on the reference return strategies is used to examine whether or not outsiders who imitate insider behaviour are able to profit from it. The major findings are as follows: firstly, announcements about the sale of stocks by insiders convey no information to market participants. Secondly, a statistically significant market response to insider disclosures of purchases of stocks in their own company can be observed in the three days prior to the announcement release for both return as well as trading volume series, and finally, outsiders who purchased stocks previously bought by insiders experience negative returns whereas outsiders disposing of stocks previously sold by insiders earned a return of 8.57% over the 6 month-period.      

CAPM with fuzzy returns and hypothesis testing

Over the last four decades, several estimation issues of the beta have been discussed extensively in many articles. An emerging consensus is that the betas are time-dependent and their estimates are impacted by the return interval and the length of the estimation period. These findings lead to the prominence of the practical implementation of the Capital Asset Pricing Model. Our goal in this paper is two-fold. After studying the impact of the return interval on the beta estimates, we analyze the sample size effects on the preceding estimation. Working in the framework of fuzzy set theory, we first associate the returns based on closing prices with the intraperiod volatility for the representation by the means of a fuzzy random variable in order to incorporate the effect of the interval period over which the returns are measured in the analysis. Next, we use these fuzzy returns to estimate the beta via fuzzy least square method in order to deal efficiently with outliers in returns, often caused by structural breaks and regime switches in the asset prices. A bootstrap test is carried out to investigate whether there is a linear relationship between the market portfolio fuzzy return and the given asset fuzzy return. Finally, the empirical results on French stocks suggest that our beta estimates seem to be more stable than the ordinary least square (OLS) estimates when the return intervals and the sample size change.